iPOGS: A 10-member ensemble of CESM HR RCP 6.0 (2006-2100) simulations

d651008
 
Abstract:

Current predictions and projections of future sea-level changes are based on Coupled Model Intercomparison Project (CMIP) class climate model simulations. Although this class of models is capable of simulating global sea-level rise and its basic spatial patterns, they are unable to robustly and accurately predict or project future regional and local sea-level changes because of their limitations in representing complex coastline and bathymetry features and regional ocean circulations with their coarse (approximately 100 km) horizontal resolutions. More specifically, sea-level changes within the Gulf of Mexico are closely linked to changes in the Loop Current and its eddies, which cannot be resolved by these CMIP-class models.

To address this fundamental issue, we have completed a 10-member ensemble of simulations with the Community Earth System Model (CESM) at a Tropical Cyclone-permitting and ocean-mesoscale-eddy-rich horizontal resolution (hereafter simply referred to as CESM-HR). The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).

Following the protocol for the CMIP phase 5 (CMIP5) experiments, the representative concentration pathway 6.0 (RCP 6.0) was used to force the model from 2006 to 2100. RCP 6.0 represents a stabilization scenario, where the greenhouse gas emission rate is high initially, but total radiative forcing is stabilized after 2100 through the use of various technologies and strategies for reducing emissions. In this scenario, the specified amount of carbon concentration results in an average global radiative forcing increase of 6.0 W/m^2 by 2100. This CESM-HR ensemble was completed as part of our National Academy of Sciences (NAS) funded project entitled "Improving Prediction and Projection of Gulf of Mexico Sea-Level Changes Using Eddy-Resolving Earth System Models (iPOGS)". This effort is complementary to the 10-member ensemble of CESM-HR historical and future (with RCP 8.5 forcing) climate simulations produced by our National Science Foundation (NSF) funded project entitled "Understanding the role of mesoscale atmosphere-ocean interactions in seasonal-to-decadal climate prediction (MESACLIP)". Each RCP 6.0 simulation starts at the end of the corresponding historical simulation from MESACLIP, enabling the exploration of future projections associated with varying levels of mitigation and future greenhouse gas emissions. For example, the figure below shows the global-mean dynamical sea level (DSL) from simulations under different forcings. The stronger warming associated with the RCP 8.5 forcing results in an additional 10 cm rise in global-mean DSL by 2100 compared to that of the RCP 6.0 ensemble.

Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Acknowledgement:

Funding:

The 10-member RCP 6.0 ensemble was completed with support from the National Academies of Science and the Gulf Research Program grant number 2000013283.

HPC Resources:

We acknowledge the Texas Advanced Computing Center (TACC; http://www.tacc.utexas.edu) at The University of Texas at Austin (UT Austin) for providing HPC resources on Frontera. We also acknowledge high-performance computing support on Derecho: HPE Cray EX System provided by NSF NCAR's Computational and Information Systems Laboratory (CISL), sponsored by NSF.

Temporal Range:
2006-01 to 2100-12
Variables:
Rain
Data Types:
Grid
Data Contributors:
TAMU/OCEAN
Department of Oceanography, Texas A&M University
 |  UCAR/NCAR/CGD
Climate and Global Dynamics Division, National Center for Atmospheric Research, University Corporation for Atmospheric Research
Publications:
Chang, P., D. Fu, X. Liu, F. S. Castruccio, A. F. Prein, G. Danabasoglu, X. Wang, J. Bacmeister, N. Rosenbloom, T. King, and S. C. Bates, 2025: Enhancing Global Climate Model Resolution to Improve Extreme Precipitation Projections. Nature, 0, 00-000.
Chang, P., Zhang, S., Danabasoglu, G., Yeager, S. G., Fu, H., Wang, H., F. S. Castruccio et al., 2020: An unprecedented set of high-resolution earth system simulations for understanding multiscale interactions in climate variability and change. Journal of Advances in Modeling Earth Systems, 12(12), 01-52.
Total Volume:
489.93 TB (Entire dataset) Volume details by dataset product
Data Formats:
Related RDA Datasets:
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MESACLIP: A 10-member ensembles of CESM HR historical (1920-2005) simulations
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MESACLIP: CESM HR RCP85 (2006-2100) 10-member ensemble
Metadata Record:
Data License:
Citation counts are compiled through information provided by publicly-accessible APIs according to the guidelines developed through the https://makedatacount.org/ project. If journals do not provide citation information to these publicly-accessible services, then this citation information will not be included in RDA citation counts. Additionally citations that include dataset DOIs are the only types included in these counts, so legacy citations without DOIs, references found in publication acknowledgements, or references to a related publication that describes a dataset will not be included in these counts.